Abstract Congenital heart disease (CHD) affects approximately 1.2% of children and is the leading cause of birth defect- related deaths. Single ventricle heart disease (SVHD) is a severe form of CHD, with high morbidity and mortality. These patients require multiple palliative surgeries, culminating with a total cavopulmonary anastomosis. Despite considerable improvement in the survival of patients with SVHD, there is increasing morbidity and mortality over time. It remains unclear why some SVHD patients fail their surgical repairs while others remain relatively well. Clinicians often rely on 2-dimensional (2D) images acquired from echocardiograms, catheterizations, or cardiovascular magnetic resonance (CMR) exams to assess SVHD patients and qualitatively choose the optimal surgical repair. The 2D images, however, lead to a suboptimal understanding of the complex 3D spatial relationships and hemodynamics, and limit efficient decision making. To address this deficiency, a free-breathing sequence is developed to acquire 3D cine CMR images of the heart and great vessels in 10 minutes. The 3D block of data will be used to generate a patient-specific pulsatile heart model. This heart model will be used to simulate the patient cardiovascular system with a lumped- parameter model. The lumped-parameter model will be used to simulate different surgical repairs and quantitatively choose the most optimal repair for each patient. We expect that this platform rationalizes surgeons' decisions for the best surgical approach and improves the survival rate of patients with SVHD.